Research Scientist Intern, Embodied Foundation Models (Data, Modeling, & Reasoning)

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

About us

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.

In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

About the Role

Our team is seeking a talented Applied Scientist Intern to join us for 3-6 months and propel our ambitious research in embodied foundation models forward.

We’re a team of Applied Scientists, Machine Learning Engineers, and Software Engineers who strive to expand the horizons of embodied AI beyond simply reacting to perceptual inputs toward reasoning over them to handle even the most complex and rare situations. Our projects encompass some of the hardest problems in AI and require leveraging the latest research, state-of-the-art models, rigorous engineering, and cross-functional collaboration.

In this role, you might:

• Work on foundation models for embodied AI, including large-scale pretraining, post-training, leveraging language, or improving reasoning capabilities.

• Train models on large-scale multimodal (vision, language, etc.) data efficiently in a multi-node distributed system, and evaluate their performance on open (and closed) datasets/benchmarks.

• Lead a high-impact research work and publish at a top tier conference (e.g., CVPR, ICCV, CoRL, NeurIPS, CoLM, RSS, ICRA, among others).

You’d be a great match for this role if:

• You have previous experience in vision-language models, large language models, natural language processing, especially around reasoning.

• You have solid software engineering fundamentals, especially in Python

• You have previously used PyTorch or a similar library for deep learning (e.g. Tensorflow, JAX).
Experience with multi-node distributed training of large models.

• You are interested in using large-scale multimodal (vision, language, etc.) datasets to improve embodied AI.

• You have previous publications in the following conferences (e.g., CVPR, ICCV, CoRL, NeurIPS, CoLM, RSS, ICRA, among others).

Essentials:

• You are currently pursuing a graduate degree in a Computer Science, Machine Learning, Robotics, or related technical field.

• You are proficient in at least one backend/systems programming language (e.g. Python, Ruby, Java, etc).

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.